Python Data Analytics
Apress (Verlag)
978-1-4842-3912-4 (ISBN)
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This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation
Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data.
What You'll Learn
Understand the core concepts of data analysis and the Python ecosystem
Go in depth with pandas for reading, writing, and processing data
Use tools and techniques for data visualization and image analysis
Examine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorch
Who This Book Is For
Experienced Python developers who need to learn about Pythonic tools for data analysis
Fabio Nelli is an IT Scientific Application Specialist at IRBM Science Park, a private research center in Pomezia, Roma, Italy. He has been a computer consultant for many years at IBM, EDS, Merck Sharp, and Dohme, along with several banks and insurance companies. He has an Organic Chemistry degree and many years of experience in Information technologies and Automation systems applied to Life Sciences (Tech Specialist at Beckman Coulter Italy and Spain). He is currently developing Java applications that interface Oracle databases with scientific instrumentation generating data and web server applications providing analysis of the results to researchers in real time.
Python Data Analytics
1. An Introduction to Data Analysis
2. Introduction to the Python's World
3. The NumPy Library
4. The pandas Library-- An Introduction
5. pandas: Reading and Writing Data
6. pandas in Depth: Data Manipulation
7. Data Visualization with matplotlib
8. Machine Learning with scikit-learn
9. Deep Learning with TensorFlow
10. An Example - Meteorological Data
11. Embedding the JavaScript D3 Library in IPython Notebook
12. Recognizing Handwritten Digits
13. Textual data Analysis with NLTK
14. Image Analysis and Computer Vision with OpenCV
Appendix A
Appendix B
| Erscheinungsdatum | 16.10.2018 |
|---|---|
| Zusatzinfo | 648 Illustrations, black and white; XIX, 569 p. 648 illus. |
| Verlagsort | Berkley |
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Gewicht | 1112 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Informatik ► Programmiersprachen / -werkzeuge ► Python | |
| Mathematik / Informatik ► Informatik ► Software Entwicklung | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Data Analysis • Data Visualization • Deep learning • Image Analysis • Keras • machine learning • OpenCV • PyTorch • Social Media Analysis • social network analysis • tensorflow • Text Mining • Theano |
| ISBN-10 | 1-4842-3912-1 / 1484239121 |
| ISBN-13 | 978-1-4842-3912-4 / 9781484239124 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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